mirror of
https://github.com/RobTillaart/Arduino.git
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227 lines
3.9 KiB
C++
227 lines
3.9 KiB
C++
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//
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// FILE: GST.cpp
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// VERSION: 0.1.1
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// PURPOSE: Arduino library for Gold Standard Test metrics
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// URL: https://github.com/RobTillaart/GST
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// https://en.wikipedia.org/wiki/Sensitivity_and_specificity
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// https://en.wikipedia.org/wiki/Confusion_matrix
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//
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// formula's based upon Wikipedia.
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#include "GST.h"
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GST::GST()
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{
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clearAll();
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};
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///////////////////////////////////////////////////////
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//
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// INPUT FUNCTIONS
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//
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void GST::setTruePositive(float v)
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{
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TP = v;
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AP = TP + FN;
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};
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void GST::setTrueNegative(float v)
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{
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TN = v;
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AN = TN + FP;
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};
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void GST::setFalsePositive(float v)
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{
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FP = v;
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AN = TN + FP;
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};
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void GST::setFalseNegative(float v)
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{
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FN = v;
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AP = TP + FN;
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};
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void GST::clearAll()
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{
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AP = 0;
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AN = 0;
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TP = 0;
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TN = 0;
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FP = 0;
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FN = 0;
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}
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// These are used for updating the test matrix
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float GST::addTruePositive(float v)
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{
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TP += v;
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AP = TP + FN;
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return TP;
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};
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float GST::addTrueNegative(float v)
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{
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TN += v;
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AN = TN + FP;
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return TN;
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};
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float GST::addFalsePositive(float v)
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{
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FP += v;
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AN = TN + FP;
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return FP;
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};
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float GST::addFalseNegative(float v)
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{
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FN += v;
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AP = TP + FN;
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return FN;
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};
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///////////////////////////////////////////////////////
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//
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// OUTPUT FUNCTIONS I
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//
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float GST::getTruePositive() { return TP; };
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float GST::getTrueNegative() { return TN; };
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float GST::getFalsePositive() { return FP; };
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float GST::getFalseNegative() { return FN; };
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float GST::getTotal() { return AP + AN; };
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float GST::getActualPositive() { return AP; };
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float GST::getActualNegative() { return AN; };
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float GST::getTestedPositive() { return TP + FP; };
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float GST::getTestedNegative() { return TN + FN; };
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float GST::sensitivity() { return TPR(); };
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float GST::specificity() { return TNR(); };
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float GST::truePositiveRate() { return TPR(); };
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float GST::TPR() { return TP / AP; };
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float GST::trueNegativeRate() { return TNR(); };
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float GST::TNR() { return TN / AN; };
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float GST::falseNegativeRate() { return FNR(); };
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float GST::FNR() { return FN / AP; };
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float GST::falsePositiveRate() { return FPR(); };
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float GST::FPR() { return FP / AN; };
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///////////////////////////////////////////////////////
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//
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// OUTPUT FUNCTIONS II
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//
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float GST::positivePredictiveValue() { return PPV(); };
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float GST::PPV() { return TP / (TP + FP); };
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float GST::negativePredictiveValue() { return NPV(); };
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float GST::NPV() { return TN / (TN + FN); };
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float GST::falseDiscoveryRate() { return FDR(); };
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float GST::FDR() { return FP / (TP + FP); };
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float GST::falseOmissionRate() { return FOR(); };
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float GST::FOR() { return FN / (TN + FN); };
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float GST::positiveLikelihoodRatio() { return LRplus(); };
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float GST::LRplus() { return TPR() / FPR(); };
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float GST::negativeLikelihoodRatio() { return LRminus(); };
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float GST::LRminus() { return FNR() / TNR(); };
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float GST::prevalenceThreshold()
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{
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return sqrt(FPR()) / (sqrt(TPR()) + sqrt(FPR()));
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};
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float GST::threatScore()
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{
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return TP / (TP + FN + FP);
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};
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float GST::criticalSuccessIndex()
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{
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return threatScore();
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};
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float GST::prevalence()
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{
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return AP / (AP + AN);
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};
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float GST::accuracy()
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{
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return (TP + TN) / (AP + AN);
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};
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float GST::balancedAccuracy()
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{
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return (TPR() + TNR()) * 0.5;
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};
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float GST::F1Score()
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{
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return (2 * TP) / (2 * TP + FP + FN);
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};
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float GST::MatthewsCorrelationCoefficient() { return MCC(); };
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float GST::phi() { return MCC(); };
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float GST::MCC()
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{
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return (TP*TN - FP*FN)/sqrt((TP+FP) * (TP+FN) * (TN+FP) * (TN+FN));
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};
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float GST::FowlkesMallowsIndex() { return FM(); };
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float GST::FM()
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{
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return sqrt(PPV()*TPR());
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};
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float GST::BookmakerInformedness() { return BM(); };
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float GST::BM()
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{
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return TPR() + TNR() - 1;
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};
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float GST::markedness() { return MK(); };
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float GST::deltaP() { return MK(); };
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float GST::MK()
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{
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return PPV() + NPV() - 1;
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};
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float GST::diagnosticOddsRatio() { return DOR(); };
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float GST::DOR()
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{
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return LRplus() / LRminus();
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};
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// -- END OF FILE --
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